| Time：1150325 (Wed.) 14:20~16:20 Speaker：Prof.高英哲(KAO, Ying-Jer) 國立臺灣大學物理學系/Department of Physics, National Taiwan University Title：Synergy of Machine Learning, Physics and Quantum Computation Abstract： In this talk, I will discuss how the fusion of machine learning, physics, and quantum computation has opened new frontiers in scientific discovery and computational efficiency. Machine learning algorithms, particularly reinforcement learning and generative modeling, have been instrumental in optimizing quantum circuits and uncovering physical structures through renormalization techniques. In quantum machine learning, variational quantum circuits combined with quantum-inspired tensor networks provide a novel framework for quantum machine learning on near-term quantum devices, enabling efficient handling of high-dimensional input data. Moreover, machine-learning-driven renormalization group techniques have been developed to automatically extract relevant physical features, facilitating the study of complex many-body systems and critical phenomena. Finally, I will discuss potential applications of generative AI in physics research. Place：S101, Gongguan Campus, NTNU |
